---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: wolof-finetuned-ner
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# wolof-finetuned-ner

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3950
- Precision: 0.7821
- Recall: 0.8912
- F1: 0.8331
- Accuracy: 0.9849

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 226  | 0.4169          | 0.7590    | 0.8571 | 0.8051 | 0.9842   |
| No log        | 2.0   | 452  | 0.3715          | 0.7738    | 0.8844 | 0.8254 | 0.9856   |
| 0.5031        | 3.0   | 678  | 0.3746          | 0.7550    | 0.9014 | 0.8217 | 0.9840   |
| 0.5031        | 4.0   | 904  | 0.3983          | 0.7651    | 0.8639 | 0.8115 | 0.9840   |
| 0.0962        | 5.0   | 1130 | 0.3950          | 0.7821    | 0.8912 | 0.8331 | 0.9849   |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3